91 lines
3.7 KiB
Python
91 lines
3.7 KiB
Python
from __future__ import annotations
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import csv
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import json
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from pathlib import Path
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from typing import Optional
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from app.services.interviews.base import PersonaRecord, MemoryDigest
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class FileSystemPersonaProvider:
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"""Reads OASIS profiles from the simulation's `reddit_profiles.json` and/or `twitter_profiles.csv`.
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If both are present, agents from `reddit_profiles.json` take precedence; twitter-only agents are appended.
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"""
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def __init__(self, reddit_path: Optional[Path], twitter_path: Optional[Path]):
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self.reddit_path = Path(reddit_path) if reddit_path else None
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self.twitter_path = Path(twitter_path) if twitter_path else None
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def _load_reddit(self) -> list[PersonaRecord]:
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if not self.reddit_path or not self.reddit_path.exists():
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return []
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data = json.loads(self.reddit_path.read_text(encoding="utf-8"))
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out = []
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for row in data:
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out.append(PersonaRecord(
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agent_id=int(row.get("user_id")),
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name=str(row.get("name") or row.get("user_name") or f"agent_{row.get('user_id')}"),
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persona=str(row.get("persona") or row.get("bio") or ""),
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profession=row.get("profession"),
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bio=row.get("bio"),
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))
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return out
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def _load_twitter(self) -> list[PersonaRecord]:
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if not self.twitter_path or not self.twitter_path.exists():
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return []
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out = []
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with self.twitter_path.open("r", encoding="utf-8", newline="") as f:
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for row in csv.DictReader(f):
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if not row.get("user_id"):
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continue
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out.append(PersonaRecord(
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agent_id=int(row["user_id"]),
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name=str(row.get("name") or row.get("user_name") or f"agent_{row['user_id']}"),
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persona=str(row.get("persona") or row.get("bio") or ""),
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profession=row.get("profession"),
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bio=row.get("bio"),
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))
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return out
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def all(self) -> list[PersonaRecord]:
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reddit = self._load_reddit()
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seen = {p.agent_id for p in reddit}
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twitter = [p for p in self._load_twitter() if p.agent_id not in seen]
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return reddit + twitter
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class ZepMemoryProvider:
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"""Builds a bounded memory digest per agent from Zep entity context.
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Maps `agent_id` (OASIS user_id) to a Zep entity UUID; falls back to the agent_id as a string.
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"""
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def __init__(self, entity_reader, graph_id: str, agent_to_entity: dict[int, str] | None = None):
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self.reader = entity_reader
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self.graph_id = graph_id
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self.map = dict(agent_to_entity or {})
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def get_digest(self, agent_id: int, max_chars: int = 2000) -> MemoryDigest:
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entity_uuid = self.map.get(agent_id) or str(agent_id)
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try:
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ctx = self.reader.get_entity_with_context(self.graph_id, entity_uuid)
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except Exception:
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return MemoryDigest(text=f"[no memory for agent {agent_id}]", available=False)
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parts: list[str] = []
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name = getattr(ctx, "name", None)
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summary = getattr(ctx, "summary", None)
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if name:
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parts.append(f"Name: {name}")
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if summary:
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parts.append(f"Summary: {summary}")
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edges = getattr(ctx, "related_edges", []) or []
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for e in edges[:20]:
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fact = e.get("fact") if isinstance(e, dict) else getattr(e, "fact", None)
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if fact:
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parts.append(f"- {fact}")
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text = "\n".join(parts)
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if len(text) > max_chars:
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text = text[: max_chars - 1] + "…"
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return MemoryDigest(text=text or f"[empty memory for agent {agent_id}]", available=True)
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